|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: es_fi_all_quy |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# es_fi_all_quy |
|
|
|
This model is a fine-tuned version of [nouman-10/es_fi_all_quy](https://huggingface.co/nouman-10/es_fi_all_quy) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4691 |
|
- Bleu: 1.3097 |
|
- Chrf: 33.573 |
|
- Gen Len: 42.0221 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 2e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:-------:| |
|
| 0.2653 | 0.09 | 1000 | 0.4870 | 1.3376 | 32.1158 | 43.001 | |
|
| 0.2668 | 0.17 | 2000 | 0.4826 | 1.3753 | 32.002 | 46.505 | |
|
| 0.2567 | 0.26 | 3000 | 0.4820 | 1.2717 | 31.9404 | 46.7274 | |
|
| 0.2561 | 0.34 | 4000 | 0.4825 | 1.4256 | 32.4758 | 41.7274 | |
|
| 0.2618 | 0.43 | 5000 | 0.4850 | 1.6935 | 33.2306 | 37.2012 | |
|
| 0.2705 | 0.51 | 6000 | 0.4723 | 1.372 | 32.4431 | 46.84 | |
|
| 0.2681 | 0.6 | 7000 | 0.4758 | 1.4419 | 32.8507 | 45.6016 | |
|
| 0.2629 | 0.68 | 8000 | 0.4737 | 1.4636 | 33.3288 | 40.0382 | |
|
| 0.2773 | 0.77 | 9000 | 0.4715 | 1.2296 | 33.1241 | 41.502 | |
|
| 0.2702 | 0.85 | 10000 | 0.4663 | 1.2579 | 32.8273 | 44.9034 | |
|
| 0.2683 | 0.94 | 11000 | 0.4694 | 1.6207 | 32.8479 | 42.3964 | |
|
| 0.259 | 1.02 | 12000 | 0.4766 | 1.4934 | 32.6413 | 41.0815 | |
|
| 0.2537 | 1.11 | 13000 | 0.4713 | 1.7586 | 33.3814 | 39.9638 | |
|
| 0.2516 | 1.19 | 14000 | 0.4724 | 1.593 | 33.4105 | 41.832 | |
|
| 0.2574 | 1.28 | 15000 | 0.4749 | 1.3373 | 33.3664 | 42.3662 | |
|
| 0.2523 | 1.37 | 16000 | 0.4701 | 1.1924 | 32.6157 | 42.7706 | |
|
| 0.2462 | 1.45 | 17000 | 0.4710 | 1.5688 | 33.5992 | 40.5282 | |
|
| 0.2513 | 1.54 | 18000 | 0.4723 | 1.2722 | 32.1578 | 47.4225 | |
|
| 0.2504 | 1.62 | 19000 | 0.4728 | 1.3897 | 32.6709 | 40.8893 | |
|
| 0.2502 | 1.71 | 20000 | 0.4714 | 1.5999 | 33.6673 | 41.5362 | |
|
| 0.2434 | 1.79 | 21000 | 0.4715 | 1.9393 | 33.6971 | 40.8944 | |
|
| 0.2483 | 1.88 | 22000 | 0.4688 | 1.8308 | 34.1117 | 37.7565 | |
|
| 0.2435 | 1.96 | 23000 | 0.4693 | 1.8643 | 34.5409 | 38.6237 | |
|
| 0.2377 | 2.05 | 24000 | 0.4702 | 1.6217 | 33.6401 | 40.4779 | |
|
| 0.235 | 2.13 | 25000 | 0.4707 | 1.5441 | 33.588 | 39.8974 | |
|
| 0.2345 | 2.22 | 26000 | 0.4710 | 2.0248 | 33.7469 | 37.2535 | |
|
| 0.2423 | 2.3 | 27000 | 0.4691 | 1.9699 | 33.4757 | 37.9889 | |
|
| 0.2388 | 2.39 | 28000 | 0.4669 | 1.5651 | 33.1965 | 39.7646 | |
|
| 0.2367 | 2.47 | 29000 | 0.4682 | 1.69 | 33.9955 | 38.3199 | |
|
| 0.2392 | 2.56 | 30000 | 0.4720 | 1.9972 | 33.902 | 41.2525 | |
|
| 0.2382 | 2.65 | 31000 | 0.4721 | 2.0682 | 33.6693 | 38.3833 | |
|
| 0.2373 | 2.73 | 32000 | 0.4690 | 2.0952 | 33.553 | 38.3229 | |
|
| 0.2356 | 2.82 | 33000 | 0.4691 | 1.3097 | 33.573 | 42.0221 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.1 |
|
- Pytorch 2.0.0+cu117 |
|
- Datasets 2.11.0 |
|
- Tokenizers 0.13.3 |
|
|
